Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration

M. Üney, K. Copsey, S. Page, B. Mulgrew, Paul Thomas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

The range of applications in which sensor networks can be deployed depends heavily on the ease with which sensor locations/orientations can be registered and the accuracy of this process. We present a scalable strategy for algorithmic network calibration using sensor measurements from non-cooperative objects. Specifically, we use recently developed separable likelihoods in order to scale with the number of sensors whilst capturing the overall uncertainties. We demonstrate the efficacy of our self-configuration solution using a real network of radar and lidar sensors for perimeter protection and compare the accuracy achieved to manual calibration.
Original languageUndefined/Unknown
Title of host publication2018 SPIE Defense and Security, Signal Processing, Sensor/Information Fusion, and Target Recognition
Pages10646 - 10646 - 13
Publication statusPublished - 27 Apr 2018
EventSPIE Defense + Commerical Sensing 2018 - Gaylord Palms Resort & Convention Center, Orlando, United States
Duration: 15 Apr 201819 Apr 2018


ConferenceSPIE Defense + Commerical Sensing 2018
Country/TerritoryUnited States
Internet address

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